gocek.org is pleased to present weather observations and forercasts with custom software developed in a living room.
Visitors can retrieve information on any named place in the US and Puerto Rico, by name or zip code. The usual land forecasts are
available as well as marine forecasts with wave heights. Our detailed predictions for precipitation are difficult to
find on most weather sites, for reasons we don't understand.

Observations are retrieved via
National Oceanographic and Atmospheric Administration (NOAA, the National weather service)
from weather stations (usually at airports) associated with the International Civil
Aviation Authority (ICAO). "Point" forecasts are provided by NOAA and predict conditions at any latitude/longitude location.
The "feels" values shows wind-chill or heat-index temperatures. Note that wind direction is described with respect to where it
blows from, so the arrow on the chart for a west wind points to the east.
Sometimes the NWS forecast shows liquid precipitation values and sub-freezing temperatures, but no snow
forecast. I don't know why, but usually, the liquid amount in these cases is small.
Data for place names and zip codes is provided by various US government sources.

Some forum traffic around the Internet mentions problems with the NWS feed, and I have worked around
some issues. There are commercial feeds that are more robust in some ways, but I figure that we taxpayers are
paying for the government data, and there's more data that I can even display on my site, so I have stayed
with the government feeds. And overall, it's pretty reliable. Try clearing your browser cache if you think you see old values

A while back, this site presented "Gary's Snowfall Formula (GSF)", an attempt to calculate predicted snowfall based on other
available predictions. This turned out to be unreliable, but here are some historical notes.

blizzard-20071216

Through various measurements, forecasters predict liquid precipitation which
falls as snow during cold weather. The amount of snow per amount of water is
the snow ratio. Traditionally, a 10:1 ratio (10 inches of snow per inch
of liquid precipitation) has been used as an approximation, but the actual
ratio depends on several factors and can be much lower or higher. Ratios higher
than 20:1 are unusual, but not unprecedented in western NY. Dense (wet, heavy)
snow produces less snow per amount of liquid precipitation than low density
(light, fluffy) snow. In 2002,
Roebber et al
described a neural network method that results in a table
of probabilities, e.g., an 80% chance of an inch of snow and a 20% chance of
two inches, and the snow ratio is now calculated with this and similar complex formulas.

The US National Weather Service sometimes
provides a liquid precipitation prediction with no snowfall prediction, even
when the predicted temperature is below freezing. In these cases, I still want
my table to show a snowfall prediction. The Roebber method uses match
techniques that are more sophisticated than I have been willing to code up to
now, so I developed a custom formula (Gary's Snow Formula, GSF) based on
Roebber's principles. In practice, GSF shows lower predictions than the NWS.
Actual snowfall is difficult to measure in the first place due to settling,
melting and sublimation (the process by which ice and snow change directly to
water vapor without first melting, i.e., icicles can disappear when the
temperature is below freezing). The snow ratio can vary widely across a small
geographic area, and large bodies of water affect the ratio, also known as
"lake effect snow".

The big northeast storms of February, 2007 buried the Tug Hill plateau north of
Syracuse, and later Chicago and Cleveland. The earlier lake effect storms
largely spared my webcam location, and the NWS point forecasts over-predicted
snowfall. The point forecasts for the later Nor'easter (in which warm, moist,
southerly air pushed into an arctic cold front) predicted a 30:1 snow ratio. My
lat/lon observation was that the NWS over-predicted the early-storm snowfall,
under-predicted the late-storm snowfall, and slightly over-predicted the total.
My GSF badly under-predicted the snowfall from the unusual combination of
single-digit temperatures and near-100% humidity.

GSF first calculates a predicted snow density factor.
Begin with 1 for Jan/Feb, 2 for Nov/Dec/Mar/Apr, 3 for Oct, 4 for May/Jun/Jul/Aug/Sep.
Add [((temperature + 15) * 2) / 25]
Add [relHum / 25]
Add [(windSpd * 2) / 25]
To account for the effect of the Great Lakes, subtract 1 from the density if
the wind direction is nearly NW, and subtract 0.5 if the direction is between
WNW and N, but this is admittedly an approximation and is optimized for
Rochester.
Based on expectations of maximum and minimum temperatures and wind speeds, the
density should be between 0 and 16, and the resulting snow ratio is based on a
typical ratio of 9 inches of snow per inch of water.
ratio = 81 / density
snowfall = predicted liquid * ratio